Due to its advantages such as ubiquity and immediacy, mobile banking has attracted traditional banks’ interests. However, a survey report showed that user adoption of mobile banking was much lower than that of other mobile services. The extant research focuses on explaining user adoption from technology perceptions such as perceived usefulness, perceived ease of use, interactivity, and relative advantage. However, users’ adoption is determined not only by their perception of the technology but also by the task technology fit. In other words, even though a technology may be perceived as being advanced, if it does not fit users’ task requirements, they may not adopt it. By integrating the task technology fit (TTF) model and the unified theory of acceptance and usage of technology (UTAUT), this research proposes a mobile banking user adoption model. We found that performance expectancy, task technology fit, social influence, and facilitating conditions have significant effects on user adoption. In addition, we also found a significant effect of task technology fit on performance expectancy.